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Article
Genome-enabled prediction for sparse testing in multi-environmental wheat trials
(CSSA; Wiley, 2021)
Article
Genomic prediction of genotype x environment interaction kernel regression models
(Crop Science Society of America, 2016)
In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel. In this ...
Article
Bayesian genomic prediction with genotype x environment interaction kernel models
(Genetics Society of America, 2017)
The phenomenon of genotype · environment (G · E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G · E have been ...
Article
Deep kernel for genomic and near infrared predictions in multi-environment breeding trials
(Genetics Society of America, 2019)
Kernel methods are flexible and easy to interpret and have been successfully used in genomic-enabled prediction of various plant species. Kernel methods used in genomic prediction comprise the linear genomic best linear ...
Article
Modeling genotype × environment interaction using a factor analytic model of on-farm wheat trials in the Yaqui Valley of Mexico
(American Society of Agronomy, 2019)
On‐farm trials of bread and durum wheat in the Yaqui Valley region of southern Sonora, Mexico, were established for three cropping seasons (2012, 2013, and 2015) using the management practices implemented by farmers. The ...
Article
Multivariate bayesian analysis of on-farm trials with multiple-trait and multiple-environment data
(American Society of Agronomy, 2019)